Ma, Yuan; Kleemann, Timm; Ziegler, Jürgen:
Psychological User Characteristics and Meta-Intents in a Conversational Product Advisor
In: Interfaces and Human Decision Making for Recommender Systems 2022 : Proceedings of the 9th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems / Brusilovsky, Peter; Gemmis, Marco de; Felfernig, Alexander; Lops, Pasquale; Polignano, Marco; Semeraro, Giovanni; Willemsen, Martijn C. (Eds.). - 9th Joint Workshop on Interfaces and Human Decision Making for Recommender Systems (IntRS 2022), 22. September 2022, hybrid Event: online & Seattle - Aachen: RWTH Aachen, 2022 - (CEUR Workshop Proceedings ; 3222), pp. 18 - 32
2022book article/chapter in ProceedingsOA Diamond
Computer ScienceFaculty of Engineering » Computer Science and Applied Cognitive Science » Computer Science » Interactive Systems
Title in English:
Psychological User Characteristics and Meta-Intents in a Conversational Product Advisor
Author:
Ma, YuanUDE;Kleemann, TimmUDE;Ziegler, JürgenUDE
Open Access?:
OA Diamond
Scopus ID
Language of text:
English
Keyword, Topic:
conversational UI design, interactive behavior analysis, decision making, influence of psychological factors on interaction
Type of resource:
Text

Abstract in English:

We present a study investigating psychological characteristics of users of a GUI-style conversational recommender system in a real-world application case. We collected data of 496 customers of an online shop using a conversational product advisor (CPA), using questionnaire responses concerning decision- making style and a set of meta-intents, a concept we propose to represent high-level user preferences related to the decision process in a CPA. We also analyzed anonymized data on users’ interactions in the CPA. Concerning general decision-making style, we could identify two clusters of users who differ in their scores on scales measuring rational and intuitive decision-making. We found evidence that rationality and intuitiveness scores are differently correlated with the proposed meta-intents such as efficiency orientation, interest in detail, and openness for guidance. Relations with interaction data could be observed between rationality/intuitiveness scores and overall time spent in the CPA. Trying to classify users’ decision style from their interactions, however did not yield positive results. Despite the limitation that only a single CPA was studied in a single domain, our results provide evidence that the proposed meta-intents are linked to the general decision-making style of a user and can thus be instrumental in translating general decision-making factors into more concrete design guidance for CPA and their potential personalization.